article · Healthcare Analytics
Tracking both the geographic spread and timeline of COVID-19 helps identify transmission hotspots and focus healthcare interventions where they are needed most. A fractional-order diffusive epidemic model has been formulated to examine how COVID-19 spreads across space and time when vaccination programmes are active. To resolve the model, an efficient numerical approach was developed using Caputo fractional-order derivatives, accompanied by a formal analysis establishing the convergence, positivity, existence, and uniqueness of the solutions. Numerical simulations demonstrate the feasibility of the computational framework for physical scenarios, evaluating how disease dynamics respond to varying rates of vaccine uptake and distribution. The findings confirm that the technique provides an effective computational tool to simulate epidemic progression and assess the broader impacts of vaccination rollouts on virus containment.
Understanding how infections move across both geography and time allows public health planners to pinpoint transmission hotspots. By simulating how vaccine rollout strategies alter disease patterns, mathematical tools can help decision-makers determine optimal intervention targets to slow the spread of infectious illnesses.
The computational method could support epidemiological modelling software used by public health analysts and epidemic forecasting agencies to evaluate vaccination strategies. Based strictly on the abstract, the work is at an early theoretical and numerical stage, relying on mathematical analysis and simulated scenarios rather than operational field-testing or deployment within active healthcare management systems.
AI-generated from the published abstract. Always read the original work before citing.
The spatiotemporal spread of COVID-19 has had a great impact on understanding and addressing the global pandemic. Through analysis of the geographical distribution and temporal patterns of the virus, the hotspot of the virus can be easily detected, giving insights into where intervention is most needed. In this study, an efficient method is presented for solving a fractional-order diffusive epidemic model of COVID-19 that incorporates vaccination and is applied to study the spatiotemporal spread of the disease. The method’s convergence is discussed, and the results are found to be applicable and efficient for numerical simulations. The proposed mathematical model is analyzed for its positivity, existence, and uniqueness of solution to demonstrate its feasibility to study physical problems, and a series of numerical simulations are conducted to analyze the spatiotemporal dynamics of COVID-19 in response to vaccine uptake and distribution modeled using the Caputo fractional order derivative. The impact of vaccine uptake and distribution is extensively discussed, and conclusions are drawn.
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DOI: 10.1016/j.health.2023.100230
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